煤炭资源开发外部成本估算模型

本文系统分析了煤炭资源开发外部成本的影响因素，探讨了煤资源开发外部成本的组成，初步建立了煤炭资源开发部成本的估算模型。     

2000~2019年中国PM2.5时空演化特征

本研究利用PM_2.5实测数据、MERRA-2 AOD与PM_2.5再分析数据、气象因子和夜间灯光等数据,基于极限梯度提升、梯度提升、随机森林模型和Stacking模型融合技术提出了PM_2.5浓度组合估算模型.在此基础上,从年、季、月尺度综合分析了2000~2019年中国PM_2.5时空变化特征.结果表明：①组合模型实现了中国2000年以来PM_2.5逐月浓度的可靠估算.②2000~2019年中国PM_2.5年均浓度呈快速增加保持稳定显著下降的趋势,2007年和2014年分别为增加到稳定和稳定到下降的转折点.PM_2.5月均浓度呈先降后升的"U"型趋势,最小值在7月,最大值在12月.③自然地理条件和人类活动奠定了中国PM_2.5浓度年度空间格局变化的基础,气象条件的逐月变化决定了PM_2.5浓度月度空间格局变化的主基调.④2000~2014年中国PM_2.5浓度的标准差椭圆中心向东移动,2014~2018年椭圆中心向西移动.1~3月椭圆中心向西移动,4~9月椭圆中心先北移后南移,9~12月椭圆中心向东移动.     

不同尺度下蒸散量测算方法的应用及展望

在水资源日益稀缺的背景下,蒸散作为陆地水循环的重要组成部分,对水资源管理和农业灌溉方案的制定都起着决定性作用。在全球尺度上,蒸散量整体呈现出了明显的随时间增加趋势,但区域尺度及流域尺度的蒸散变化则呈现出较大的不确定性,并且在一些下垫面比较复杂的地区,如喀斯特小流域,蒸散作为流域水循环的重要组成部分往往难以准确测定,所以更需要因地制宜地选择蒸散量测算方法。基于此,本文以各种方法的研究尺度为切入点,将当前被广泛接受的蒸散研究方法分为小尺度方法,即针对单体植株和适用于田块尺度的蒸散研究方法,包括树干液流法、零通量面法、风调室法、蒸渗仪法以及土壤-植被-大气连续体(SPAC)水分传输综合模拟法;百米尺度方法,包括波文比法和涡动相关法;公里尺度方法,主要包括闪烁仪法;流域及区域尺度方法,包括水量平衡法和空间遥感法。概述了各个方法的应用范围、特点以及局限性,列举了前人工作中各种方法之间的对比验证,着重分析了闪烁仪方法在复杂下垫面的应用前景,以便在不同研究条件和研究尺度下能选择最佳的蒸散量测算方法,并对未来蒸散研究进行了展望。     

Imputing Unmeasured Explanatory Variables in Environmental Epidemiology With Application to Health Impact Analysis of Air Pollution

This paper presents the results of a reconsideration of earlier work that finds an association between daily hospital admissions for respiratory distress and daily concentrations of sulphate (lag 1) as well as daily maximum concentrations of ozone (lags 1 and 3). These associations are found even after clustering the data by hospital of admission and accounting for the effects of temperature. We use an adaptation of their generalized estimating equation technique for clustered data, that daily data being for southern Ontario summers from 1983 to 1988. Like them, we adjust for daily maximum temperatures. However, unlike the earlier work returned to ours includes daily average humidity as a potential explanatory variable in our model. Our analysis also differs from theirs in that we cluster the data by census subdivision to reduce the risk of confounding pollutant levels with population size within regions. Moreover, we log-transform the explanatory variables and then high-pass filter the resulting data. We also deviate from the earlier analysis by taking account of measurement error incurred in using surrogate measures of the explanatory variables. To do so we use new methodology designed for our study but of potential value in other applications. That methodology requires a spatial predictive distribution for the unmeasured explanatory variables. Each day about 700 missing measurements for each of these variables can then be imputed over the geographical domain of the study. With these imputations we get a measure of imputation error through the covariance of the predictive distribution. Along with the predictive distribution we require an impact model to link-up with the predictive distribution. We describe that model and show how it uses the imputed measurements of the missing values of the explanatory variables. We also show how through that model, uncertainty about these values is reflected in our analysis and in commensurate uncertainties in the inferences made. Apart from its substantive objectives, our analysis serves to test the new methods with the earlier results serving as a foil. The reassuring qualitative agreement between our findings and the earlier results seems encouraging.     

生态系统价值核算指标体系研究

生态系统价值核算是开展生态系统保护成效评估的重要手段,也是支撑生态文明制度体系建设的关键技术之一.指标体系的设定是开展生态系统价值核算的重要前提和基础,但当前生态系统价值还缺少统一的核算指标,因此,在一定程度上制约了生态系统价值在生态系统管理与决策中的应用.在总结归纳当前生态系统价值相关指标体系的基础上,以服务于生态系统管理和相关绩效考核为目标,提出了包括生物生产性、人类收益性、保护成效性、实际发生性、实物度量性、数据可获性、持续更新性、非危害性在内的8项生态系统价值核算原则,筛选形成了包括7个功能类别、15个一级科目和26个二级科目的生态系统价值核算指标体系,并针对实物量达到一定数值才能形成服务的指标设定了核算基准.以厦门市为例探讨了这一指标体系的应用能力,其不仅包括了厦门市主要生态系统服务,而且体现了厦门市作为沿海旅游城市的区域特色.在此基础上,探索了开展生态系统价值统计核算的可能途径,主要包括建立生态系统价值统计核算公式,编制技术导则,开展培训、制定定期发布制度等,旨在为实现生态系统价值的业务核算及其应用提供技术支撑.      

2004年春夏季河北海域叶绿素a分布和初级生产力估算

2004年春季5月和夏季8月进行的河北海洋资源调查研究表明:全海域春季5月表层叶绿素a介于0.34～11,39mg/m3,平均值为3.72 mg/m3,底层叶绿素a介于0.87～7.85 mg/m3,平均值为3.03 mg/m3;夏季8月表层叶绿素a介于1.1～18.3 mg/m3,平均值为4.52 mg/m3,底层叶绿素a介于0.4～7.8 mg/m3,平均值为3.95 mg/m3.初级生产力(以C计)春季5月介于112.26～1323.68 mg/m2·d,平均值为504.79 mg/m2·d,夏季8月介于83.92～4265.73 mg/m2·d,平均值为774.96 mg/m2·d.总体趋势是南部海区(沧州海区)叶绿素a含量高于北部海区(秦皇岛、唐山海区)叶绿素a含量,秦皇岛海区初级生产力估算值最高,唐山海区最低.     

基于卫星遥感数据(AOD)估算PM2.5的研究进展

雾霾天气的频繁出现,不断向人们警示中国大气环境污染的严重性.细颗粒物PM2.5作为空气质量评价指标之一,由于粒径小、为有毒性物质提供载体的特性,对人们的健康和生活产生很大的负面影响.近年来,PM2.5的相关研究引起了世界各国研究者的广泛关注,通过地基手段获得PM2.5质量浓度受到环境、地理等因素的限制,而利用卫星遥感技术估算地面PM2.5质量浓度,覆盖面广、估算精度可靠,对环境污染监测和治理具有重要意义.在综合了国内外关于气溶胶光学厚度(AOD)估算PM2.5文献的基础上,对AOD和PM2.5的数据源和估算的方法及手段作了简要介绍,分析总结了AOD与PM2.5相关性与PM2.5遥感估算的模型,并展望了未来PM2.5研究的发展方向.     

Estimating the population size with a behavioral response in capture-recapture experiment

A new estimating procedure is suggested to estimate the population size in a capture-recapture experiment. The capture intensities for first-capture and recapture are allowed to be different and time dependent but they are assumed to be proportional. It is shown that the information on the proportionality constant is crucial to the estimation of the population size. Sensitivity analysis with a misspecification of the proportionality constant is conducted. The method has also been extended to the case with an unknown proportionality. A real example is given.     

尾矿库伴生放射性污染清除水平估算研究

通过RESRAD程序模拟估算了某尾矿库伴生放射性污染清除水平,同时对尾矿库中的232 Th模拟估算参数进行设定,并对剂量约束限值的确定、照射情景分析、照射途径设定、模式参数设定、计算机模拟估算清除水平及估算结果分析等进行了分析研究。结果表明,此尾矿库中232 Th及其长寿命子体所致最大年有效剂量约为10.7mSv/a,超出了预设的0.25mSv/a的剂量约束限值;致癌风险0.023 5,远超出人们的可接受水平;当在剂量约束限值为0.25mSv/a时,此尾矿库土壤中的232 Th清除水平为0.047Bq/g。通过分析表明,该尾矿库开放前,必须采取一定措施,进行清除工作。     

Regression analysis of forest damage by marginal models for correlated ordinal responses

Studies on forest damage generally cannot be carried out by common regression models, for two main reasons: Firstly, the response variable, damage state of trees, is usually observed in ordered categories. Secondly, responses are often correlated, either serially, as in a longitudinal study, or spatially, as in the application of this paper, where neighbourhood interactions exist between damage states of spruces determined from aerial pictures. Thus so-called marginal regression models for ordinal responses, taking into account dependence among observations, are appropriate for correct inference. To this end we extend the binary models of Liang and Zeger (1986) and develop an ordinal GEEI model, based on parametrizing association by global cross-ratios. The methods are applied to data from a survey conducted in Southern Germany. Due to the survey design, responses must be assumed to be spatially correlated. The results show that the proposed ordinal marginal regression models provide appropriate tools for analysing the influence of covariates, that characterize the stand, on the damage state of spruce.